In this paper, we present a new mathematical framework for modeling texture images using independent basic gray level aura matrices (BGLAMs). We prove that independent BGLAMs are the basis of gray level aura matrices (GLAMs), and that an image can be uniquely represented by its independent BGLAMs. We propose a new BGLAM distance measure for automatically evaluating synthesis results w.r.t. input textures to determine if the output is a successful synthesis of the input. For the application to texture synthesis, we present a new algorithm to synthesize textures by sampling only the independent BGLAMs of an input texture. With respect to synthesis of textures and evaluation of the results, the performance of our approach is extensively evaluated and compared with symmetric GLAMs that are used in existing techniques and with gray level cooccurrence matrices (GLCMs). Experimental results have shown that (1) our approach significantly outperforms both symmetric GLAMs and GLCMs; (2) the new BGLAM distance measure has the ability to evaluate synthesis results, which can be used to automate the conventional visual inspection process for determining whether or not the output texture is a successful synthesis of the input; and (3) a broad range of textures can be faithfully synthesized using independent BGLAMs and the synthesis results are comparable to existing techniques.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Basic gray level aura matrices: theory and its application to texture synthesis


    Beteiligte:
    Xuejie Qin, (Autor:in) / Yee-Hong Yang, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    547182 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Basic Gray Level Aura Matrices: Theory and its Application to Texture Synthesis

    Qin, X. / Yang, Y.-H. / IEEE | British Library Conference Proceedings | 2005


    Similarity Measure and Learning with Gray Level Aura Matrices (GLAM) for Texture Image Retrieval

    Qin, X. / Yang, Y.-H. / IEEE Computer Society | British Library Conference Proceedings | 2004



    EOS Aura

    Fisher, Dominic | NTRS | 2019


    EOS Aura

    B. Guit | NTIS | 2022